The invention disclosed and claimed herein generally pertains to an improved method and apparatus for computed tomography (CT) cone-beam imaging by means of the Radon transform, which improves efficiency in processor operation. One of the most important techniques currently used in constructing a CT image of an object is based on the Radon transform, which is of particular importance in three-dimensional (3D) CT imaging. According to such technique, a cone-beam x-ray source irradiates the object while traversing a scan path, to project an image of the object onto a detector plane. Line integral, or cone beam x-ray, data is acquired at each of a succession of views, or view positions, located along the scan path. The line integral data is converted into a set of Radon data points, or planar integrals defined in Radon space, and an inverse Radon transform is performed using the planar integrals to construct the image. The conversion process is most usefully carried out by computing the radial derivative (Radon derivative) for each planar integral in the set, from which the values of respective planar integrals can be readily determined.
Commonly assigned U.S. Pat. No. 5,257,183, issued Oct. 26, 1993 to Kwok C. Tam, the inventor named herein, discloses a very effective technique for computing the Radon derivatives for use in the above process. While this technique works quite well, a great deal of computational effort is required. In the past, this has been achieved by partitioning the Radon space by means of a set of coaxial planes, such as the set of vertical or azimuthal planes shown in FIG. 4 of the above-referenced U.S. Pat. No. 5,257,183. Each of such planes is provided with a set of grid points, and each data point in a Radon data set lies in one or another of the planes, at a grid point thereof.
To determine respective derivatives, a number of adjacent partitioning planes are typically assigned to each processor in an array of processors. For a given view position, each processor computes the Radon derivatives for the Radon data points lying in its assigned planes, from line integral data acquired at the given view. Thus, the processors can be operated in parallel, that is, simultaneously and independently from one another, to reduce time and complexity in determining the derivatives.
Notwithstanding the benefits of the above arrangement, it has been found that for a given view position, the number of Radon data points lying in respective partitioning planes, for which derivatives must be computed, can vary extensively from plane to plane. Accordingly, different processors can have very different workloads, reducing efficiency of processor operation.